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data-layer-region="article-body-header" class="mdc-u-grid mdc-u-grid-col-md-12 mck-u-animation-blur-in-400 byline-share-container"><div class="mdc-u-grid-col-md-start-2 mdc-u-grid-col-md-end-8 mdc-u-grid-col-lg-start-3 mdc-u-grid-col-lg-end-8 mdc-u-ts-9"><span> </span><span class="AuthorsByLine_mck-c-authors-byline__author__XdrlD"><span class="AuthorsByLine_mck-c-authors-byline__no-wrap__Ced0j">Eric Hazan </span></span><span class="AuthorsByLine_mck-c-authors-byline__author__XdrlD"><span class="AuthorsByLine_mck-c-authors-byline__no-wrap__Ced0j"><a data-component="mdc-c-link" href="/our-people/anu-madgavkar" class="mdc-c-link-inline___7DRrt_8032924 mdc-c-link-inline--secondary___YKoOK_8032924"><span class="mdc-c-link__label___Pfqtd_8032924">Anu Madgavkar</span></a> </span></span><span class="AuthorsByLine_mck-c-authors-byline__author__XdrlD"><span class="AuthorsByLine_mck-c-authors-byline__no-wrap__Ced0j"><a data-component="mdc-c-link" href="/our-people/michael-chui" class="mdc-c-link-inline___7DRrt_8032924 mdc-c-link-inline--secondary___YKoOK_8032924"><span class="mdc-c-link__label___Pfqtd_8032924">Michael Chui</span></a> </span></span><span class="AuthorsByLine_mck-c-authors-byline__author__XdrlD"><span class="AuthorsByLine_mck-c-authors-byline__no-wrap__Ced0j"><a data-component="mdc-c-link" href="/our-people/sven-smit" class="mdc-c-link-inline___7DRrt_8032924 mdc-c-link-inline--secondary___YKoOK_8032924"><span class="mdc-c-link__label___Pfqtd_8032924">Sven Smit</span></a> </span></span><span class="AuthorsByLine_mck-c-authors-byline__author__XdrlD"><span class="AuthorsByLine_mck-c-authors-byline__no-wrap__Ced0j"><a data-component="mdc-c-link" href="/our-people/dana-maor" class="mdc-c-link-inline___7DRrt_8032924 mdc-c-link-inline--secondary___YKoOK_8032924"><span class="mdc-c-link__label___Pfqtd_8032924">Dana Maor</span></a> </span></span><span class="AuthorsByLine_mck-c-authors-byline__author__XdrlD"><span class="AuthorsByLine_mck-c-authors-byline__no-wrap__Ced0j">Gurneet Singh Dandona<span> </span></span></span><span class="AuthorsByLine_mck-c-authors-byline__author__XdrlD"><span class="AuthorsByLine_mck-c-authors-byline__no-wrap__Ced0j">Roland Huyghues-Despointes</span></span></div><div class="mdc-u-grid-col-md-start-8 mdc-u-grid-col-md-end-12 mdc-u-grid-col-lg-start-8 mdc-u-grid-col-lg-end-11 ArticleContent_mck-c-article-content__share-tools__kWRRw"></div></section><section class="mdc-u-grid mdc-u-grid-col-md-12 mck-u-animation-blur-in-400"><div class="mdc-u-grid-col-md-start-2 mdc-u-grid-col-md-end-12 mdc-u-grid-col-lg-start-3 mdc-u-grid-col-lg-end-11"><div data-component="mdc-c-description" class="mdc-c-description___SrnQP_8032924 mdc-u-ts-5"><div class="mck-u-links-inline">To gain the full productivity benefits of generative AI and other technologies, Europe and the United States will need to focus both on improving human capital and accelerating technology adoption.</div></div></div></section><main data-layer-region="article-body" class="mdc-u-grid mdc-u-grid-gutter-xxl"><div class="mdc-u-grid mdc-u-grid-col-1 mdc-u-grid-col-md-12"><div class="mdc-u-grid-col-md-start-2 mdc-u-grid-col-md-end-12 mdc-u-grid-col-lg-start-3 mdc-u-grid-col-lg-end-11"><div class="mdc-o-content-body mck-u-dropcap"><div data-component="mdc-c-module-wrapper" data-module-theme="default" data-module-background="transparent" data-module-category="" class="DownloadsSidebar_mck-c-downloads-sidebar__iFmyt mck-o-xs-right-span"><div data-layer-region="downloads-right-rail"><h3 data-component="mdc-c-heading" class="mdc-c-heading___0fM1W_8032924 mdc-c-heading--title___5qyOB_8032924 mdc-c-heading--border___K8dj3_8032924"></h3><div><div data-component="mdc-c-link-container" class="mdc-c-link-container___xefGu_8032924"><a data-component="mdc-c-link" href="#/download/%2F~%2Fmedia%2Fmckinsey%2Fmckinsey%20global%20institute%2Four%20research%2Fa%20new%20future%20of%20work%20the%20race%20to%20deploy%20ai%20and%20raise%20skills%20in%20europe%20and%20beyond%2Fa-new-future-of-work-the-race-to-deploy-ai-and-raise-skills-in-europe-and-beyond.pdf%3FshouldIndex%3Dfalse" class="DownloadsSidebar_mck-c-downloads-sidebar__download-link__fPqFQ mdc-c-link___lBbY1_8032924" target="_self" data-layer-event-prefix="Download Link" data-layer-action="click" data-layer-report-type="" data-layer-file-name="a-new-future-of-work-the-race-to-deploy-ai-and-raise-skills-in-europe-and-beyond" data-layer-report-name="a-new-future-of-work-the-race-to-deploy-ai-and-raise-skills-in-europe-and-beyond>"><span data-component="mdc-c-icon" class="mdc-c-icon___oi7ef_8032924 mdc-c-icon--size-md___yi5fA_8032924 mck-download-icon"></span><span class="mdc-c-link__label___Pfqtd_8032924"> (68 pages)</span></a></div></div></div></div> <h2>At a glance</h2> <p><strong>Amid tightening labor markets and a slowdown in productivity growth, Europe and the United States face shifts in labor demand, spurred by AI and automation.</strong> Our updated modeling of the future of work finds that demand for workers in STEM-related, healthcare, and other high-skill professions would rise, while demand for occupations such as office workers, production workers, and customer service representatives would decline. By 2030, in a midpoint adoption scenario, up to 30 percent of current hours worked could be automated, accelerated by generative AI (gen AI). Efforts to achieve net-zero emissions, an aging workforce, and growth in e-commerce, as well as infrastructure and technology spending and overall economic growth, could also shift employment demand.</p> <p><strong>By 2030, Europe could require up to 12 million occupational transitions, double the prepandemic pace.</strong> In the United States, required transitions could reach almost 12 million, in line with the prepandemic norm. Both regions navigated even higher levels of labor market shifts at the height of the COVID-19 period, suggesting that they can handle this scale of future job transitions. The pace of occupational change is broadly similar among countries in Europe, although the specific mix reflects their economic variations.</p> <p><strong>Businesses will need a major skills upgrade.</strong> Demand for technological and social and emotional skills could rise as demand for physical and manual and higher cognitive skills stabilizes. Surveyed executives in Europe and the United States expressed a need not only for advanced IT and data analytics but also for critical thinking, creativity, and teaching and training—skills they report as currently being in short supply. Companies plan to focus on retraining workers, more than hiring or subcontracting, to meet skill needs.</p> <p><strong>Workers with lower wages face challenges of redeployment as demand reweights toward occupations with higher wages in both Europe and the United States.</strong> Occupations with lower wages are likely to see reductions in demand, and workers will need to acquire new skills to transition to better-paying work. If that doesn’t happen, there is a risk of a more polarized labor market, with more higher-wage jobs than workers and too many workers for existing lower-wage jobs.</p> <p><strong>Choices made today could revive productivity growth while creating better societal outcomes.</strong> Embracing the path of accelerated technology adoption with proactive worker redeployment could help Europe achieve an annual productivity growth rate of up to 3 percent through 2030. However, slow adoption would limit that to 0.3 percent, closer to today’s level of productivity growth in Western Europe. Slow worker redeployment would leave millions unable to participate productively in the future of work.</p> <div data-component="mdc-c-module-wrapper" data-module-theme="default" data-module-background="transparent" data-module-category="" class="mck-o-xl-full-width Image_mck-c-image__fhx5v"><picture data-component="mdc-c-picture" class="Image_mck-c-image__img-container__JusDB"><source media="(min-width: 768px)" srcSet="/~/media/mckinsey/mckinsey%20global%20institute/our%20research/a%20new%20future%20of%20work%20the%20race%20to%20deploy%20ai%20and%20raise%20skills%20in%20europe%20and%20beyond/gettyimages-1090693290_ca.jpg?cq=50&mw=1180&cpy=Center"/><img alt="Businessman and skilled worker in high tech enterprise, using VR glasses - stock photo" src="/~/media/mckinsey/mckinsey%20global%20institute/our%20research/a%20new%20future%20of%20work%20the%20race%20to%20deploy%20ai%20and%20raise%20skills%20in%20europe%20and%20beyond/gettyimages-1090693290_ca.jpg?cq=50&mw=767&cpy=Center" loading="lazy"/></picture><div class="mck-u-sr-only">Businessman and skilled worker in high tech enterprise, using VR glasses - stock photo</div></div> <h2>Demand will change for a range of occupations through 2030, including growth in STEM- and healthcare-related occupations, among others</h2> <p>This report focuses on labor markets in nine major economies in the European Union along with the United Kingdom, in comparison with the United States. Technology, including most recently the rise of gen AI, along with other factors, will spur changes in the pattern of labor demand through 2030. Our study, which uses an updated version of the McKinsey Global Institute future of work model, seeks to quantify the occupational transitions that will be required and the changing nature of demand for different types of jobs and skills.</p> <div data-component="mdc-c-module-wrapper" data-module-theme="light" data-module-background="lightest-grey" data-module-category="" data-module-gradient-position="bottom-right" class="mck-c-inline-module-container SideBar_mck-c-sidebar__bgimg-wrapper__Qj4Dt mck-o-sm-left-span SideBar_mck-c-sidebar__sidebar-wrapper__Dpjw2 SideBar_mck-c-sidebar__sidebar-wrapper--istablet__IQ6ii mck-u-screen-only mck-c-module-wrapper" data-layer-region="sidebar"><div class="SideBar_mck-c-sidebar__epoAm mck-o-md-center"><div class="SideBar_mck-c-sidebar__share-icons-wrapper__9gB_c"><div data-component="mdc-c-link-container" class="mdc-c-link-container___xefGu_8032924 mdc-c-link-container--display-column___X0HDD_8032924 SideBar_mck-c-sidebar__share-icons___eQy6"><div data-component="mdc-c-dropdown-menu" class="mdc-c-drop-down"><button data-component="mdc-c-button" aria-label="" type="button" id="button_id" class="mdc-c-button___U4iY2_8032924 mdc-c-button--ghost mdc-c-button--size-medium mdc-c-drop-down__rootmenu___yJzvz_8032924" aria-expanded="false" aria-haspopup="menu"><span data-component="mdc-c-icon" class="mdc-c-icon___oi7ef_8032924 mdc-c-icon--default___f-hQM_8032924 mdc-c-icon--size-md___yi5fA_8032924 mck-share2-icon"></span></button><div data-component="mdc-c-module-wrapper" data-module-theme="light" data-module-background="white" data-module-category="" class=""></div></div><button data-component="mdc-c-button" aria-label="Expandable Sidebar" type="button" id="button_id" class="mdc-c-button___U4iY2_8032924 mdc-c-button--ghost mdc-c-button--size-medium SideBar_mck-c-sidebar__toggle-btn__EL8iE" aria-expanded="false" data-layer-event-prefix="UI Item" data-layer-action="click" data-layer-category="sidebar" data-layer-subcategory="open" data-layer-text="open sidebar"><span data-component="mdc-c-icon" class="mdc-c-icon___oi7ef_8032924 mdc-c-icon--radial___y3csX_8032924 mdc-c-icon--size-xxl___cL3ZT_8032924 mck-plus-no-circle-icon"></span></button></div></div><div class="SideBar_mck-c-sidebar__content-outer__UdWCq"><div class="SideBar_mck-c-sidebar__eyebrow__5GSEq"></div><div class="SideBar_mck-c-sidebar__content__raEwe"><h2 data-component="mdc-c-heading" class="mdc-c-heading___0fM1W_8032924 mdc-u-ts-3 SideBar_mck-c-sidebar__content-heading__NJekY"><div>Our methodology</div></h2><div class="SideBar_mck-c-sidebar__content-description__4p9iI mdc-u-ts-7"><div class="mdc-o-content-body"><p>We used methodology consistent with other McKinsey Global Institute reports on the future of work to model trends of job changes at the level of occupations, activities, and skills. For this report, we focused our analysis on the 2022–30 period.</p> <p>Our model estimates net changes in employment demand by sector and occupation; we also estimate occupational transitions, or the net number of workers that need to change in each type of occupation, based on which occupations face declining demand by 2030 relative to current employment in 2022. We included ten countries in Europe: nine EU members—the Czech Republic, Denmark, France, Germany, Italy, Netherlands, Poland, Spain, and Sweden—and the United Kingdom. For the United States, we build on estimates published in our 2023 report Generative AI and the future of work in America.</p> <p>We included multiple drivers in our modeling: automation potential, net-zero transition, e-commerce growth, remote work adoption, increases in income, aging populations, technology investments, and infrastructure investments.</p> <p>Two scenarios are used to bookend the work-automation model: “late” and “early.” For Europe, we modeled a “faster” scenario and a “slower” one. For the faster scenario, we use the midpoint—the arithmetical average between our late and early scenarios. For the slower scenario, we use a “mid late” trajectory, an arithmetical average between a late adoption scenario and the midpoint scenario. For the United States, we use the midpoint scenario, based on our earlier research.</p> <p>We also estimate the productivity effects of automation, using GDP per full-time-equivalent (FTE) employee as the measure of productivity. We assumed that workers displaced by automation rejoin the workforce at 2022 productivity levels, net of automation, and in line with the expected 2030 occupational mix.</p></div></div></div></div></div></div> <p>Amid tightening labor markets and a slowdown in productivity growth, Europe and the United States face shifts in labor demand, spurred not only by AI and automation but also by other trends, including efforts to achieve net-zero emissions, an aging population, infrastructure spending, technology investments, and growth in e-commerce, among others (see sidebar, “Our methodology”).</p> <p>Our analysis finds that demand for occupations such as health professionals and other STEM-related professionals would grow by 17 to 30 percent between 2022 and 2030, (Exhibit 1).</p> <div data-component="mdc-c-module-wrapper" data-module-theme="default" data-module-background="transparent" data-module-category="" class="mck-c-inline-module-container mck-o-md-center"><div class="mck-c-content-header"><div class="ContentHeader_mck-c-content-header__eyebrow__cBTe_"></div></div><div class="mck-u-inline-module-border-bottom"><picture data-component="mdc-c-picture" class="Exhibit_mck-c-exhibit__image__pyIDm"><source media="(min-width: 768px)" srcSet="/~/media/mckinsey/mckinsey%20global%20institute/our%20research/a%20new%20future%20of%20work%20the%20race%20to%20deploy%20ai%20and%20raise%20skills%20in%20europe%20and%20beyond/svgz_mck242172-vivatech-2024_exh1.svgz?cq=50&cpy=Center"/><img alt="Demand for healthcare and STEM roles could grow, while demand for office support and customer service roles could decline." src="/~/media/mckinsey/mckinsey%20global%20institute/our%20research/a%20new%20future%20of%20work%20the%20race%20to%20deploy%20ai%20and%20raise%20skills%20in%20europe%20and%20beyond/svgz_mck242172-vivatech-2024_exh1.svgz?cq=50&cpy=Center" loading="lazy"/></picture></div><div class="mck-u-sr-only"></div></div> <p>By contrast, demand for workers in food services, production work, customer services, sales, and office support—all of which declined over the 2012–22 period—would continue to decline until 2030. These jobs involve a high share of repetitive tasks, data collection, and elementary data processing—all activities that automated systems can handle efficiently.</p> <h2>Up to 30 percent of hours worked could be automated by 2030, boosted by gen AI, leading to millions of required occupational transitions</h2> <p>By 2030, our analysis finds that about 27 percent of current hours worked in Europe and 30 percent of hours worked in the United States could be automated, accelerated by gen AI. Our model suggests that roughly 20 percent of hours worked could still be automated even without gen AI, implying a significant acceleration.</p> <p>These trends will play out in labor markets in the form of workers needing to change occupations. By 2030, under the faster adoption scenario we modeled, Europe could require up to 12.0 million occupational transitions, affecting 6.5 percent of current employment. That is double the prepandemic pace (Exhibit 2). Under a slower scenario we modeled for Europe, the number of occupational transitions needed would amount to 8.5 million, affecting 4.6 percent of current employment. In the United States, required transitions could reach almost 12.0 million, affecting 7.5 percent of current employment. Unlike Europe, this magnitude of transitions is broadly in line with the prepandemic norm.</p> <div data-component="mdc-c-module-wrapper" data-module-theme="default" data-module-background="transparent" data-module-category="" class="mck-c-inline-module-container mck-o-md-center"><div class="mck-c-content-header"><div class="ContentHeader_mck-c-content-header__eyebrow__cBTe_"></div></div><div class="mck-u-inline-module-border-bottom"><picture data-component="mdc-c-picture" class="Exhibit_mck-c-exhibit__image__pyIDm"><source media="(min-width: 768px)" srcSet="/~/media/mckinsey/mckinsey%20global%20institute/our%20research/a%20new%20future%20of%20work%20the%20race%20to%20deploy%20ai%20and%20raise%20skills%20in%20europe%20and%20beyond/svgz_mck242172-vivatech-2024_exh2-v2.svgz?cq=50&cpy=Center"/><img alt="Europe may need faster occupational transitions relative to the past, while the United States could return to its prepandemic pace." src="/~/media/mckinsey/mckinsey%20global%20institute/our%20research/a%20new%20future%20of%20work%20the%20race%20to%20deploy%20ai%20and%20raise%20skills%20in%20europe%20and%20beyond/svgz_mck242172-vivatech-2024_exh2-v2.svgz?cq=50&cpy=Center" loading="lazy"/></picture></div><div class="mck-u-sr-only"></div></div> <p>Both regions navigated even higher levels of labor market shifts at the height of the COVID-19 period. While these were abrupt and painful to many, given the forced nature of the shifts, the experience suggests that both regions have the ability to handle this scale of future job transitions.</p> <div data-component="mdc-c-module-wrapper" data-module-theme="default" data-module-background="transparent" data-module-category="" class="mck-o-xl-full-width Image_mck-c-image__fhx5v"><picture data-component="mdc-c-picture" class="Image_mck-c-image__img-container__JusDB"><source media="(min-width: 768px)" srcSet="/~/media/mckinsey/mckinsey%20global%20institute/our%20research/a%20new%20future%20of%20work%20the%20race%20to%20deploy%20ai%20and%20raise%20skills%20in%20europe%20and%20beyond/gettyimages-1487035179_ca.jpg?cq=50&mw=1180&cpy=Center"/><img alt="Smiling female PhD student discussing with man at desk in innovation lab - stock photo" src="/~/media/mckinsey/mckinsey%20global%20institute/our%20research/a%20new%20future%20of%20work%20the%20race%20to%20deploy%20ai%20and%20raise%20skills%20in%20europe%20and%20beyond/gettyimages-1487035179_ca.jpg?cq=50&mw=767&cpy=Center" loading="lazy"/></picture><div class="mck-u-sr-only">Smiling female PhD student discussing with man at desk in innovation lab - stock photo</div></div> <h2>Businesses will need a major skills upgrade</h2> <p>The occupational transitions noted above herald substantial shifts in workforce skills in a future in which automation and AI are integrated into the workplace (Exhibit 3). Workers use multiple skills to perform a given task, but for the purposes of our quantification, we identified the predominant skill used.</p> <div data-component="mdc-c-module-wrapper" data-module-theme="default" data-module-background="transparent" data-module-category="" class="mck-c-inline-module-container mck-o-md-center"><div class="mck-c-content-header"><div class="ContentHeader_mck-c-content-header__eyebrow__cBTe_"></div></div><div class="mck-u-inline-module-border-bottom"><picture data-component="mdc-c-picture" class="Exhibit_mck-c-exhibit__image__pyIDm"><source media="(min-width: 768px)" srcSet="/~/media/mckinsey/mckinsey%20global%20institute/our%20research/a%20new%20future%20of%20work%20the%20race%20to%20deploy%20ai%20and%20raise%20skills%20in%20europe%20and%20beyond/svgz_mck242172-vivatech-2024_exh3-v2.svgz?cq=50&cpy=Center"/><img alt="Demand for technological and social and emotional skills could increase in Europe." src="/~/media/mckinsey/mckinsey%20global%20institute/our%20research/a%20new%20future%20of%20work%20the%20race%20to%20deploy%20ai%20and%20raise%20skills%20in%20europe%20and%20beyond/svgz_mck242172-vivatech-2024_exh3-v2.svgz?cq=50&cpy=Center" loading="lazy"/></picture></div><div class="mck-u-sr-only"></div></div> <p>Demand for technological skills could see substantial growth in Europe and in the United States (increases of 25 percent and 29 percent, respectively, in hours worked by 2030 compared to 2022) under our midpoint scenario of automation adoption (which is the faster scenario for Europe).</p> <p>Demand for social and emotional skills could rise by 11 percent in Europe and by 14 percent in the United States. Underlying this increase is higher demand for roles requiring interpersonal empathy and leadership skills. These skills are crucial in healthcare and managerial roles in an evolving economy that demands greater adaptability and flexibility.</p> <p>Conversely, demand for work in which basic cognitive skills predominate is expected to decline by 14 percent. Basic cognitive skills are required primarily in office support or customer service roles, which are highly susceptible to being automated by AI. Among work characterized by these basic cognitive skills experiencing significant drops in demand are basic data processing and literacy, numeracy, and communication.</p> <p>Demand for work in which higher cognitive skills predominate could also decline slightly, according to our analysis. While creativity is expected to remain highly sought after, with a potential increase of 12 percent by 2030, work activities characterized by other advanced cognitive skills such as advanced literacy and writing, along with quantitative and statistical skills, could decline by 19 percent.</p> <p>Demand for physical and manual skills, on the other hand, could remain roughly level with the present. These skills remain the largest share of workforce skills, representing about 30 percent of total hours worked in 2022. Growth in demand for these skills between 2022 and 2030 could come from the build-out of infrastructure and higher investment in low-emissions sectors, while declines would be in line with continued automation in production work.</p> <h3>Business executives report skills shortages today and expect them to worsen</h3> <p>A survey we conducted of C-suite executives in five countries shows that companies are already grappling with skills challenges, including a skills mismatch, particularly in technological, higher cognitive, and social and emotional skills: about one-third of the more than 1,100 respondents report a shortfall in these critical areas. At the same time, a notable number of executives say they have enough employees with basic cognitive skills and, to a lesser extent, physical and manual skills.</p> <p>Within technological skills, companies in our survey reported that their most significant shortages are in advanced IT skills and programming, advanced data analysis, and mathematical skills. Among higher cognitive skills, significant shortfalls are seen in critical thinking and problem structuring and in complex information processing. About 40 percent of the executives surveyed pointed to a shortage of workers with these skills, which are needed for working alongside new technologies (Exhibit 4).</p> <div data-component="mdc-c-module-wrapper" data-module-theme="default" data-module-background="transparent" data-module-category="" class="mck-c-inline-module-container mck-o-md-center"><div class="mck-c-content-header"><div class="ContentHeader_mck-c-content-header__eyebrow__cBTe_"></div></div><div class="mck-u-inline-module-border-bottom"><picture data-component="mdc-c-picture" class="Exhibit_mck-c-exhibit__image__pyIDm"><source media="(min-width: 768px)" srcSet="/~/media/mckinsey/mckinsey%20global%20institute/our%20research/a%20new%20future%20of%20work%20the%20race%20to%20deploy%20ai%20and%20raise%20skills%20in%20europe%20and%20beyond/svgz_mck242172-vivatech-2024_exh4.svgz?cq=50&cpy=Center"/><img alt="Surveyed executives reported rising demand for technological and advanced cognitive skills, relative to their share in today’s workforce." src="/~/media/mckinsey/mckinsey%20global%20institute/our%20research/a%20new%20future%20of%20work%20the%20race%20to%20deploy%20ai%20and%20raise%20skills%20in%20europe%20and%20beyond/svgz_mck242172-vivatech-2024_exh4.svgz?cq=50&cpy=Center" loading="lazy"/></picture></div><div class="mck-u-sr-only"></div></div> <div data-component="mdc-c-module-wrapper" data-module-theme="default" data-module-background="transparent" data-module-category="" class="mck-o-xl-full-width Image_mck-c-image__fhx5v"><picture data-component="mdc-c-picture" class="Image_mck-c-image__img-container__JusDB"><source media="(min-width: 768px)" srcSet="/~/media/mckinsey/mckinsey%20global%20institute/our%20research/a%20new%20future%20of%20work%20the%20race%20to%20deploy%20ai%20and%20raise%20skills%20in%20europe%20and%20beyond/gettyimages-2012746930_ca.jpg?cq=50&mw=1180&cpy=Center"/><img alt="Two IT co-workers code on laptop or technology for testing, web design or online startup - stock photo" src="/~/media/mckinsey/mckinsey%20global%20institute/our%20research/a%20new%20future%20of%20work%20the%20race%20to%20deploy%20ai%20and%20raise%20skills%20in%20europe%20and%20beyond/gettyimages-2012746930_ca.jpg?cq=50&mw=767&cpy=Center" loading="lazy"/></picture><div class="mck-u-sr-only">Two IT co-workers code on laptop or technology for testing, web design or online startup - stock photo</div></div> <h3>Companies see retraining as key to acquiring needed skills and adapting to the new work landscape</h3> <p>Surveyed executives expect significant changes to their workforce skill levels and worry about not finding the right skills by 2030. More than one in four survey respondents said that failing to capture the needed skills could directly harm financial performance and indirectly impede their efforts to leverage the value from AI.</p> <p>To acquire the skills they need, companies have three main options: retraining, hiring, and contracting workers. Our survey suggests that executives are looking at all three options, with retraining the most widely reported tactic planned to address the skills mismatch: on average, out of companies that mentioned retraining as one of their tactics to address skills mismatch, executives said they would retrain 32 percent of their workforce. The scale of retraining needs varies in degree. For example, respondents in the automotive industry expect 36 percent of their workforce to be retrained, compared with 28 percent in the financial services industry. Out of those who have mentioned hiring or contracting as their tactics to address the skills mismatch, executives surveyed said they would hire an average of 23 percent of their workforce and contract an average of 18 percent.</p> <h3>Occupational transitions will affect high-, medium-, and low-wage workers differently</h3> <p>All ten European countries we examined for this report may see increasing demand for top-earning occupations. By contrast, workers in the two lowest-wage-bracket occupations could be three to five times more likely to have to change occupations compared to the top wage earners, our analysis finds. The disparity is much higher in the United States, where workers in the two lowest-wage-bracket occupations are up to 14 times more likely to face occupational shifts than the highest earners. In Europe, the middle-wage population could be twice as affected by occupational transitions as the same population in United States, representing 7.3 percent of the working population who might face occupational transitions.</p> <h2>Enhancing human capital at the same time as deploying the technology rapidly could boost annual productivity growth</h2> <div data-component="mdc-c-module-wrapper" data-module-theme="light" data-module-background="lightest-grey" data-module-category="" data-module-gradient-position="bottom-right" class="mck-c-inline-module-container SideBar_mck-c-sidebar__bgimg-wrapper__Qj4Dt mck-o-sm-left-span SideBar_mck-c-sidebar__sidebar-wrapper__Dpjw2 SideBar_mck-c-sidebar__sidebar-wrapper--istablet__IQ6ii mck-u-screen-only mck-c-module-wrapper" data-layer-region="sidebar"><div class="SideBar_mck-c-sidebar__epoAm mck-o-md-center"><div class="SideBar_mck-c-sidebar__share-icons-wrapper__9gB_c"><div data-component="mdc-c-link-container" class="mdc-c-link-container___xefGu_8032924 mdc-c-link-container--display-column___X0HDD_8032924 SideBar_mck-c-sidebar__share-icons___eQy6"><div data-component="mdc-c-dropdown-menu" class="mdc-c-drop-down"><button data-component="mdc-c-button" aria-label="" type="button" id="button_id" class="mdc-c-button___U4iY2_8032924 mdc-c-button--ghost mdc-c-button--size-medium mdc-c-drop-down__rootmenu___yJzvz_8032924" aria-expanded="false" aria-haspopup="menu"><span data-component="mdc-c-icon" class="mdc-c-icon___oi7ef_8032924 mdc-c-icon--default___f-hQM_8032924 mdc-c-icon--size-md___yi5fA_8032924 mck-share2-icon"></span></button><div data-component="mdc-c-module-wrapper" data-module-theme="light" data-module-background="white" data-module-category="" class=""></div></div><button data-component="mdc-c-button" aria-label="Expandable Sidebar" type="button" id="button_id" class="mdc-c-button___U4iY2_8032924 mdc-c-button--ghost mdc-c-button--size-medium SideBar_mck-c-sidebar__toggle-btn__EL8iE" aria-expanded="false" data-layer-event-prefix="UI Item" data-layer-action="click" data-layer-category="sidebar" data-layer-subcategory="open" data-layer-text="open sidebar"><span data-component="mdc-c-icon" class="mdc-c-icon___oi7ef_8032924 mdc-c-icon--radial___y3csX_8032924 mdc-c-icon--size-xxl___cL3ZT_8032924 mck-plus-no-circle-icon"></span></button></div></div><div class="SideBar_mck-c-sidebar__content-outer__UdWCq"><div class="SideBar_mck-c-sidebar__eyebrow__5GSEq"></div><div class="SideBar_mck-c-sidebar__content__raEwe"><h2 data-component="mdc-c-heading" class="mdc-c-heading___0fM1W_8032924 mdc-u-ts-3 SideBar_mck-c-sidebar__content-heading__NJekY"><div>About QuantumBlack, AI by McKinsey</div></h2><div class="SideBar_mck-c-sidebar__content-description__4p9iI mdc-u-ts-7"><div class="mdc-o-content-body"><p><strong>QuantumBlack,</strong> McKinsey’s AI arm, helps companies transform using the power of technology, technical expertise, and industry experts. With thousands of practitioners at QuantumBlack (data engineers, data scientists, product managers, designers, and software engineers) and McKinsey (industry and domain experts), we are working to solve the world’s most important AI challenges. QuantumBlack Labs is our center of technology development and client innovation, which has been driving cutting-edge advancements and developments in AI through locations across the globe.</p></div></div></div></div></div></div> <p>Organizations and policy makers have choices to make; the way they approach AI and automation, along with human capital augmentation, will affect economic and societal outcomes.</p> <p>We have attempted to quantify at a high level the potential effects of different stances to AI deployment on productivity in Europe. Our analysis considers two dimensions. The first is the adoption rate of AI and automation technologies. We consider the faster scenario and the late scenario for technology adoption. Faster adoption would unlock greater productivity growth potential but also, potentially, more short-term labor disruption than the late scenario.</p> <p>The second dimension we consider is the level of automated worker time that is redeployed into the economy. This represents the ability to redeploy the time gained by automation and productivity gains (for example, new tasks and job creation). This could vary depending on the success of worker training programs and strategies to match demand and supply in labor markets.</p> <p>We based our analysis on two potential scenarios: either all displaced workers would be able to fully rejoin the economy at a similar productivity level as in 2022 or only some 80 percent of the automated workers’ time will be redeployed into the economy.</p> <p>Exhibit 5 illustrates the various outcomes in terms of annual productivity growth rate. The top-right quadrant illustrates the highest economy-wide productivity, with an annual productivity growth rate of up to 3.1 percent. It requires fast adoption of technologies as well as full redeployment of displaced workers. The top-left quadrant also demonstrates technology adoption on a fast trajectory and shows a relatively high productivity growth rate (up to 2.5 percent). However, about 6.0 percent of total hours worked (equivalent to 10.2 million people not working) would not be redeployed in the economy. Finally, the two bottom quadrants depict the failure to adopt AI and automation, leading to limited productivity gains and translating into limited labor market disruptions.</p> <div data-component="mdc-c-module-wrapper" data-module-theme="default" data-module-background="transparent" data-module-category="" class="mck-c-inline-module-container mck-o-md-center"><div class="mck-c-content-header"><div class="ContentHeader_mck-c-content-header__eyebrow__cBTe_"></div></div><div class="mck-u-inline-module-border-bottom"><picture data-component="mdc-c-picture" class="Exhibit_mck-c-exhibit__image__pyIDm"><source media="(min-width: 768px)" srcSet="/~/media/mckinsey/mckinsey%20global%20institute/our%20research/a%20new%20future%20of%20work%20the%20race%20to%20deploy%20ai%20and%20raise%20skills%20in%20europe%20and%20beyond/svgz_mck242172-vivatech-2024_exh5.svgz?cq=50&cpy=Center"/><img alt="Europe faces choices about the pace of AI adoption and redeployment of work hours, with different social and economic outcomes." src="/~/media/mckinsey/mckinsey%20global%20institute/our%20research/a%20new%20future%20of%20work%20the%20race%20to%20deploy%20ai%20and%20raise%20skills%20in%20europe%20and%20beyond/svgz_mck242172-vivatech-2024_exh5.svgz?cq=50&cpy=Center" loading="lazy"/></picture></div><div class="mck-u-sr-only"></div></div> <div data-component="mdc-c-module-wrapper" data-module-theme="default" data-module-background="transparent" data-module-category="" class="mck-o-xl-full-width Image_mck-c-image__fhx5v"><picture data-component="mdc-c-picture" class="Image_mck-c-image__img-container__JusDB"><source media="(min-width: 768px)" srcSet="/~/media/mckinsey/mckinsey%20global%20institute/our%20research/a%20new%20future%20of%20work%20the%20race%20to%20deploy%20ai%20and%20raise%20skills%20in%20europe%20and%20beyond/gettyimages-2140495878_ca.jpg?cq=50&mw=1180&cpy=Center"/><img alt="Managers discussing work while futuristic AI computer vision analyzing, ccanning production line - stock photo" src="/~/media/mckinsey/mckinsey%20global%20institute/our%20research/a%20new%20future%20of%20work%20the%20race%20to%20deploy%20ai%20and%20raise%20skills%20in%20europe%20and%20beyond/gettyimages-2140495878_ca.jpg?cq=50&mw=767&cpy=Center" loading="lazy"/></picture><div class="mck-u-sr-only">Managers discussing work while futuristic AI computer vision analyzing, ccanning production line - stock photo</div></div> <h2>Four priorities for companies</h2> <p>The adoption of automation technologies will be decisive in protecting businesses’ competitive advantage in an automation and AI era. To ensure successful deployment at a company level, business leaders can embrace four priorities.</p> <p><em>Understand the potential.</em> Leaders need to understand the potential of these technologies, notably including how AI and gen AI can augment and automate work. This includes estimating both the total capacity that these technologies could free up and their impact on role composition and skills requirements. Understanding this allows business leaders to frame their end-to-end strategy and adoption goals with regard to these technologies.</p> <p><em>Plan a strategic workforce shift.</em> Once they understand the potential of automation technologies, leaders need to plan the company’s shift toward readiness for the automation and AI era. This requires sizing the workforce and skill needs, based on strategically identified use cases, to assess the potential future talent gap. From this analysis will flow details about the extent of recruitment of new talent, upskilling, or reskilling of the current workforce that is needed, as well as where to redeploy freed capacity to more value-added tasks.</p> <p><em>Prioritize people development.</em> To ensure that the right talent is on hand to sustain the company strategy during all transformation phases, leaders could consider strengthening their capabilities to identify, attract, and recruit future AI and gen AI leaders in a tight market. They will also likely need to accelerate the building of AI and gen AI capabilities in the workforce. Nontechnical talent will also need training to adapt to the changing skills environment. Finally, leaders could deploy an HR strategy and operating model to fit the post–gen AI workforce.</p> <p><em>Pursue the executive-education journey on automation technologies.</em> Leaders also need to undertake their own education journey on automation technologies to maximize their contributions to their companies during the coming transformation. This includes empowering senior managers to explore automation technologies implications and subsequently role model to others, as well as bringing all company leaders together to create a dedicated road map to drive business and employee value.</p> <p>AI and the toolbox of advanced new technologies are evolving at a breathtaking pace. For companies and policy makers, these technologies are highly compelling because they promise a range of benefits, including higher productivity, which could lift growth and prosperity. Yet, as this report has sought to illustrate, making full use of the advantages on offer will also require paying attention to the critical element of human capital. In the best-case scenario, workers’ skills will develop and adapt to new technological challenges. Achieving this goal in our new technological age will be highly challenging—but the benefits will be great.</p></div><div class="container-placeholder"></div></div></div><div class="mdc-u-grid mdc-u-grid-gutter-xl"><section role="contentinfo" data-layer-region="article-about-authors" class="mdc-u-grid mdc-u-grid-col-md-12 AboutAuthor_mck-c-about-author__nRJzu"><div class="mdc-u-grid-col-md-start-2 mdc-u-grid-col-md-end-12 mdc-u-grid-col-lg-start-3 mdc-u-grid-col-lg-end-11"><h5 data-component="mdc-c-heading" class="mdc-c-heading___0fM1W_8032924 mdc-c-heading--title___5qyOB_8032924 mdc-c-heading--border___K8dj3_8032924 mdc-u-align-center"></h5><div data-component="mdc-c-description" class="mdc-c-description___SrnQP_8032924 mdc-u-ts-8 mck-u-links-inline mck-u-links-inline--secondary mdc-u-mt-5"><div><p><strong><a href="/sitecore/service/notfound.aspx?item=web%3a%7ba3be299c-32b8-494d-8d01-4cc4e102c098%7d%40en">Eric Hazan</a></strong> is a McKinsey senior partner based in Paris; <strong><a href="/our-people/anu-madgavkar">Anu Madgavkar</a></strong> and <strong><a href="/our-people/michael-chui">Michael Chui</a></strong> are McKinsey Global Institute partners based in New Jersey and San Francisco, respectively; <strong><a href="/our-people/sven-smit">Sven Smit</a></strong> is chair of the McKinsey Global Institute and a McKinsey senior partner based in Amsterdam; <strong><a href="/our-people/dana-maor">Dana Maor</a></strong> is a McKinsey senior partner based in Tel Aviv; <strong>Gurneet Singh Dandona</strong> is an associate partner and a senior expert based in New York; and <strong>Roland Huyghues-Despointes</strong> is a consultant based in Paris.</p></div></div></div></section><section class="mdc-u-grid mdc-u-grid-col-md-12 mck-u-screen-only"><div class="mdc-u-grid-col-md-start-2 mdc-u-grid-col-md-end-12 mdc-u-grid-col-lg-start-5 mdc-u-grid-col-lg-end-9"><h5 data-component="mdc-c-heading" class="mdc-c-heading___0fM1W_8032924 mdc-c-heading--title___5qyOB_8032924 mdc-c-heading--border___K8dj3_8032924 mdc-u-align-center">Explore a career with us</h5><div data-component="mdc-c-link-container" class="mdc-c-link-container___xefGu_8032924 mdc-c-link-container--align-center___ar3mu_8032924"><a data-component="mdc-c-link" href="/careers/search-jobs" class="mdc-c-button___U4iY2_8032924 mdc-c-button--secondary___Boipq_8032924 mdc-c-button--size-large___jwpUy_8032924" aria-label="Search Openings" data-layer-event-prefix="CTA Link" data-layer-action="click" data-layer-category="careers" data-layer-subcategory="search" data-layer-text="Search Openings"><span class="mdc-c-link__label___Pfqtd_8032924">Search Openings</span></a></div></div></section></div></main></div><div data-component="mdc-c-module-wrapper" data-module-theme="light" data-module-background="lightest-grey" data-module-category="StandalonePromo" class="RelatedArticle_mck-c-article-related__GGA76 mck-u-screen-only" data-layer-region="related-articles"><div class="mdc-o-container__wrapper is-wrapped mdc-u-spaced-mobile"><h5 data-component="mdc-c-heading" class="mdc-c-heading___0fM1W_8032924 mdc-c-heading--title___5qyOB_8032924 mdc-u-align-center">Related Articles</h5><div class="mdc-u-grid mdc-u-grid-col-md-3 RelatedArticle_items-container__s2uD0"><div class="mdc-u-grid mdc-u-grid-gutter-lg Card_card__diA2r Card_hover-effect__RGb9b"><div class="Card_wrapper-image__8b4P6"><a data-component="mdc-c-link" href="/mgi/our-research/generative-ai-and-the-future-of-work-in-america" class="mdc-c-link___lBbY1_8032924"><picture data-component="mdc-c-picture" class="Card_wrapper-image__8b4P6"><style>.picture-uniqueKey-gener-0 { aspect-ratio: 16/9 }</style><img alt="""" class="picture-uniqueKey-gener-0" src="/~/media/mckinsey/mckinsey%20global%20institute/our%20research/generative%20ai%20and%20the%20future%20of%20work%20in%20america/the-future-of-work-mattmurphy-thumb-1536x1536.jpg?cq=50&mw=767&car=16:9&cpy=Center" loading="lazy"/></picture></a></div><div class="Card_wrapper-text__U6Y3k"><div data-component="mdc-c-content-block" class="mdc-c-content-block___7p6Lu_8032924 Card_content-block__pF6Z1"><span>Report - 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By 2030, in a midpoint adoption scenario, up to 30 percent of current hours worked could be automated, accelerated by generative AI (gen AI). Efforts to achieve net-zero emissions, an aging workforce, and growth in e-commerce, as well as infrastructure and technology spending and overall economic growth, could also shift employment demand.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBy 2030, Europe could require up to 12 million occupational transitions, double the prepandemic pace.\u003c/strong\u003e In the United States, required transitions could reach almost 12 million, in line with the prepandemic norm. Both regions navigated even higher levels of labor market shifts at the height of the COVID-19 period, suggesting that they can handle this scale of future job transitions. The pace of occupational change is broadly similar among countries in Europe, although the specific mix reflects their economic variations.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBusinesses will need a major skills upgrade.\u003c/strong\u003e Demand for technological and social and emotional skills could rise as demand for physical and manual and higher cognitive skills stabilizes. Surveyed executives in Europe and the United States expressed a need not only for advanced IT and data analytics but also for critical thinking, creativity, and teaching and training\u0026mdash;skills they report as currently being in short supply. Companies plan to focus on retraining workers, more than hiring or subcontracting, to meet skill needs.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eWorkers with lower wages face challenges of redeployment as demand reweights toward occupations with higher wages in both Europe and the United States.\u003c/strong\u003e Occupations with lower wages are likely to see reductions in demand, and workers will need to acquire new skills to transition to better-paying work. If that doesn\u0026rsquo;t happen, there is a risk of a more polarized labor market, with more higher-wage jobs than workers and too many workers for existing lower-wage jobs.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eChoices made today could revive productivity growth while creating better societal outcomes.\u003c/strong\u003e Embracing the path of accelerated technology adoption with proactive worker redeployment could help Europe achieve an annual productivity growth rate of up to 3 percent through 2030. However, slow adoption would limit that to 0.3 percent, closer to today\u0026rsquo;s level of productivity growth in Western Europe. Slow worker redeployment would leave millions unable to participate productively in the future of work.\u003c/p\u003e\n[[image 1]]\n\u003ch2\u003eDemand will change for a range of occupations through 2030, including growth in STEM- and healthcare-related occupations, among others\u003c/h2\u003e\n\u003cp\u003eThis report focuses on labor markets in nine major economies in the European Union along with the United Kingdom, in comparison with the United States. Technology, including most recently the rise of gen AI, along with other factors, will spur changes in the pattern of labor demand through 2030. Our study, which uses an updated version of the McKinsey Global Institute future of work model, seeks to quantify the occupational transitions that will be required and the changing nature of demand for different types of jobs and skills.\u003c/p\u003e\n[[sidebar 1]]\n\u003cp\u003eAmid tightening labor markets and a slowdown in productivity growth, Europe and the United States face shifts in labor demand, spurred not only by AI and automation but also by other trends, including efforts to achieve net-zero emissions, an aging population, infrastructure spending, technology investments, and growth in e-commerce, among others (see sidebar, \u0026ldquo;Our methodology\u0026rdquo;).\u003c/p\u003e\n\u003cp\u003eOur analysis finds that demand for occupations such as health professionals and other STEM-related professionals would grow by 17 to 30 percent between 2022 and 2030, (Exhibit 1).\u003c/p\u003e\n[[exhibit 1]]\n\u003cp\u003eBy contrast, demand for workers in food services, production work, customer services, sales, and office support\u0026mdash;all of which declined over the 2012\u0026ndash;22 period\u0026mdash;would continue to decline until 2030. These jobs involve a high share of repetitive tasks, data collection, and elementary data processing\u0026mdash;all activities that automated systems can handle efficiently.\u003c/p\u003e\n\u003ch2\u003eUp to 30 percent of hours worked could be automated by 2030, boosted by gen AI, leading to millions of required occupational transitions\u003c/h2\u003e\n\u003cp\u003eBy 2030, our analysis finds that about 27 percent of current hours worked in Europe and 30 percent of hours worked in the United States could be automated, accelerated by gen AI. Our model suggests that roughly 20 percent of hours worked could still be automated even without gen AI, implying a significant acceleration.\u003c/p\u003e\n\u003cp\u003eThese trends will play out in labor markets in the form of workers needing to change occupations. By 2030, under the faster adoption scenario we modeled, Europe could require up to 12.0 million occupational transitions, affecting 6.5 percent of current employment. That is double the prepandemic pace (Exhibit 2). Under a slower scenario we modeled for Europe, the number of occupational transitions needed would amount to 8.5 million, affecting 4.6 percent of current employment. In the United States, required transitions could reach almost 12.0 million, affecting 7.5 percent of current employment. Unlike Europe, this magnitude of transitions is broadly in line with the prepandemic norm.\u003c/p\u003e\n[[exhibit 2]]\n\u003cp\u003eBoth regions navigated even higher levels of labor market shifts at the height of the COVID-19 period. While these were abrupt and painful to many, given the forced nature of the shifts, the experience suggests that both regions have the ability to handle this scale of future job transitions.\u003c/p\u003e\n[[image 2]]\n\u003ch2\u003eBusinesses will need a major skills upgrade\u003c/h2\u003e\n\u003cp\u003eThe occupational transitions noted above herald substantial shifts in workforce skills in a future in which automation and AI are integrated into the workplace (Exhibit 3). Workers use multiple skills to perform a given task, but for the purposes of our quantification, we identified the predominant skill used.\u003c/p\u003e\n[[exhibit 3]]\n\u003cp\u003eDemand for technological skills could see substantial growth in Europe and in the United States (increases of 25 percent and 29 percent, respectively, in hours worked by 2030 compared to 2022) under our midpoint scenario of automation adoption (which is the faster scenario for Europe).\u003c/p\u003e\n\u003cp\u003eDemand for social and emotional skills could rise by 11 percent in Europe and by 14 percent in the United States. Underlying this increase is higher demand for roles requiring interpersonal empathy and leadership skills. These skills are crucial in healthcare and managerial roles in an evolving economy that demands greater adaptability and flexibility.\u003c/p\u003e\n\u003cp\u003eConversely, demand for work in which basic cognitive skills predominate is expected to decline by 14 percent. Basic cognitive skills are required primarily in office support or customer service roles, which are highly susceptible to being automated by AI. Among work characterized by these basic cognitive skills experiencing significant drops in demand are basic data processing and literacy, numeracy, and communication.\u003c/p\u003e\n\u003cp\u003eDemand for work in which higher cognitive skills predominate could also decline slightly, according to our analysis. While creativity is expected to remain highly sought after, with a potential increase of 12 percent by 2030, work activities characterized by other advanced cognitive skills such as advanced literacy and writing, along with quantitative and statistical skills, could decline by 19 percent.\u003c/p\u003e\n\u003cp\u003eDemand for physical and manual skills, on the other hand, could remain roughly level with the present. These skills remain the largest share of workforce skills, representing about 30 percent of total hours worked in 2022. Growth in demand for these skills between 2022 and 2030 could come from the build-out of infrastructure and higher investment in low-emissions sectors, while declines would be in line with continued automation in production work.\u003c/p\u003e\n\u003ch3\u003eBusiness executives report skills shortages today and expect them to worsen\u003c/h3\u003e\n\u003cp\u003eA survey we conducted of C-suite executives in five countries shows that companies are already grappling with skills challenges, including a skills mismatch, particularly in technological, higher cognitive, and social and emotional skills: about one-third of the more than 1,100 respondents report a shortfall in these critical areas. At the same time, a notable number of executives say they have enough employees with basic cognitive skills and, to a lesser extent, physical and manual skills.\u003c/p\u003e\n\u003cp\u003eWithin technological skills, companies in our survey reported that their most significant shortages are in advanced IT skills and programming, advanced data analysis, and mathematical skills. Among higher cognitive skills, significant shortfalls are seen in critical thinking and problem structuring and in complex information processing. About 40 percent of the executives surveyed pointed to a shortage of workers with these skills, which are needed for working alongside new technologies (Exhibit 4).\u003c/p\u003e\n[[exhibit 4]]\n[[image 3]]\n\u003ch3\u003eCompanies see retraining as key to acquiring needed skills and adapting to the new work landscape\u003c/h3\u003e\n\u003cp\u003eSurveyed executives expect significant changes to their workforce skill levels and worry about not finding the right skills by 2030. More than one in four survey respondents said that failing to capture the needed skills could directly harm financial performance and indirectly impede their efforts to leverage the value from AI.\u003c/p\u003e\n\u003cp\u003eTo acquire the skills they need, companies have three main options: retraining, hiring, and contracting workers. Our survey suggests that executives are looking at all three options, with retraining the most widely reported tactic planned to address the skills mismatch: on average, out of companies that mentioned retraining as one of their tactics to address skills mismatch, executives said they would retrain 32 percent of their workforce. The scale of retraining needs varies in degree. For example, respondents in the automotive industry expect 36 percent of their workforce to be retrained, compared with 28 percent in the financial services industry. Out of those who have mentioned hiring or contracting as their tactics to address the skills mismatch, executives surveyed said they would hire an average of 23 percent of their workforce and contract an average of 18 percent.\u003c/p\u003e\n\u003ch3\u003eOccupational transitions will affect high-, medium-, and low-wage workers differently\u003c/h3\u003e\n\u003cp\u003eAll ten European countries we examined for this report may see increasing demand for top-earning occupations. By contrast, workers in the two lowest-wage-bracket occupations could be three to five times more likely to have to change occupations compared to the top wage earners, our analysis finds. The disparity is much higher in the United States, where workers in the two lowest-wage-bracket occupations are up to 14 times more likely to face occupational shifts than the highest earners. In Europe, the middle-wage population could be twice as affected by occupational transitions as the same population in United States, representing 7.3 percent of the working population who might face occupational transitions.\u003c/p\u003e\n\u003ch2\u003eEnhancing human capital at the same time as deploying the technology rapidly could boost annual productivity growth\u003c/h2\u003e\n[[globalsidebar QB]]\n\u003cp\u003eOrganizations and policy makers have choices to make; the way they approach AI and automation, along with human capital augmentation, will affect economic and societal outcomes.\u003c/p\u003e\n\u003cp\u003eWe have attempted to quantify at a high level the potential effects of different stances to AI deployment on productivity in Europe. Our analysis considers two dimensions. The first is the adoption rate of AI and automation technologies. We consider the faster scenario and the late scenario for technology adoption. Faster adoption would unlock greater productivity growth potential but also, potentially, more short-term labor disruption than the late scenario.\u003c/p\u003e\n\u003cp\u003eThe second dimension we consider is the level of automated worker time that is redeployed into the economy. This represents the ability to redeploy the time gained by automation and productivity gains (for example, new tasks and job creation). This could vary depending on the success of worker training programs and strategies to match demand and supply in labor markets.\u003c/p\u003e\n\u003cp\u003eWe based our analysis on two potential scenarios: either all displaced workers would be able to fully rejoin the economy at a similar productivity level as in 2022 or only some 80 percent of the automated workers\u0026rsquo; time will be redeployed into the economy.\u003c/p\u003e\n\u003cp\u003eExhibit 5 illustrates the various outcomes in terms of annual productivity growth rate. The top-right quadrant illustrates the highest economy-wide productivity, with an annual productivity growth rate of up to 3.1 percent. It requires fast adoption of technologies as well as full redeployment of displaced workers. The top-left quadrant also demonstrates technology adoption on a fast trajectory and shows a relatively high productivity growth rate (up to 2.5 percent). However, about 6.0 percent of total hours worked (equivalent to 10.2 million people not working) would not be redeployed in the economy. Finally, the two bottom quadrants depict the failure to adopt AI and automation, leading to limited productivity gains and translating into limited labor market disruptions.\u003c/p\u003e\n[[exhibit 5]]\n[[image 4]]\n\u003ch2\u003eFour priorities for companies\u003c/h2\u003e\n\u003cp\u003eThe adoption of automation technologies will be decisive in protecting businesses\u0026rsquo; competitive advantage in an automation and AI era. To ensure successful deployment at a company level, business leaders can embrace four priorities.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eUnderstand the potential.\u003c/em\u003e Leaders need to understand the potential of these technologies, notably including how AI and gen AI can augment and automate work. This includes estimating both the total capacity that these technologies could free up and their impact on role composition and skills requirements. Understanding this allows business leaders to frame their end-to-end strategy and adoption goals with regard to these technologies.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003ePlan a strategic workforce shift.\u003c/em\u003e Once they understand the potential of automation technologies, leaders need to plan the company\u0026rsquo;s shift toward readiness for the automation and AI era. This requires sizing the workforce and skill needs, based on strategically identified use cases, to assess the potential future talent gap. From this analysis will flow details about the extent of recruitment of new talent, upskilling, or reskilling of the current workforce that is needed, as well as where to redeploy freed capacity to more value-added tasks.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003ePrioritize people development.\u003c/em\u003e To ensure that the right talent is on hand to sustain the company strategy during all transformation phases, leaders could consider strengthening their capabilities to identify, attract, and recruit future AI and gen AI leaders in a tight market. They will also likely need to accelerate the building of AI and gen AI capabilities in the workforce. Nontechnical talent will also need training to adapt to the changing skills environment. Finally, leaders could deploy an HR strategy and operating model to fit the post\u0026ndash;gen AI workforce.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003ePursue the executive-education journey on automation technologies.\u003c/em\u003e Leaders also need to undertake their own education journey on automation technologies to maximize their contributions to their companies during the coming transformation. This includes empowering senior managers to explore automation technologies implications and subsequently role model to others, as well as bringing all company leaders together to create a dedicated road map to drive business and employee value.\u003c/p\u003e\n\u003cp\u003eAI and the toolbox of advanced new technologies are evolving at a breathtaking pace. For companies and policy makers, these technologies are highly compelling because they promise a range of benefits, including higher productivity, which could lift growth and prosperity. Yet, as this report has sought to illustrate, making full use of the advantages on offer will also require paying attention to the critical element of human capital. In the best-case scenario, workers\u0026rsquo; skills will develop and adapt to new technological challenges. Achieving this goal in our new technological age will be highly challenging\u0026mdash;but the benefits will be great.\u003c/p\u003e"},"isFullScreenInteractive":{"boolValue":false},"hideStickySocialShareBar":{"boolValue":false},"desktopID":{"value":""},"mobileID":{"value":""},"desktopURL":{"value":""},"mobileURL":{"value":""},"desktopPaddingPercentage":{"value":""},"mobilePaddingPercentage":{"value":""},"desktopOverrideHeight":{"value":""},"mobileOverrideHeight":{"value":""},"cerosOembedURL":{"value":""},"cerosRenderMode":{"targetItem":null},"cerosBackgroundColor":{"targetItem":null},"hideByLine":{"boolValue":false},"tableOfContentsTitle":{"value":"TABLE OF CONTENTS"},"accessStatus":{"targetItem":{"key":{"value":"RegisteredUsers"},"value":{"value":"Registered Users"}}},"articleType":{"targetItem":{"displayName":"Report"}},"hasSpecialReport":{"boolValue":false},"contentType":{"targetItem":{"displayName":"Article"}},"sourcePublication":{"targetItem":{"name":"MGI Research","displayName":"MGI Research","title":{"value":"MGI Research"},"relatedlinks":{"url":"/mgi/overview"},"landinglinks":{"jsonValue":{"value":[]}}}},"externalPublication":{"value":""},"excludeFromClientLink":{"boolValue":false},"originalPublishDate":{"jsonValue":{"value":"2024-05-21T00:00:00Z"}},"footnotes":{"value":""},"contributoryPractice":{"targetItems":[{"displayName":"McKinsey Global Institute"}]},"aboutTheAuthors":{"value":"\u003cp\u003e\u003cstrong\u003e\u003ca href=\"/sitecore/service/notfound.aspx?item=web%3a%7ba3be299c-32b8-494d-8d01-4cc4e102c098%7d%40en\"\u003eEric Hazan\u003c/a\u003e\u003c/strong\u003e is a McKinsey senior partner based in Paris; \u003cstrong\u003e\u003ca href=\"/our-people/anu-madgavkar\"\u003eAnu Madgavkar\u003c/a\u003e\u003c/strong\u003e and \u003cstrong\u003e\u003ca href=\"/our-people/michael-chui\"\u003eMichael Chui\u003c/a\u003e\u003c/strong\u003e are McKinsey Global Institute partners based in New Jersey and San Francisco, respectively; \u003cstrong\u003e\u003ca href=\"/our-people/sven-smit\"\u003eSven Smit\u003c/a\u003e\u003c/strong\u003e is chair of the McKinsey Global Institute and a McKinsey senior partner based in Amsterdam; \u003cstrong\u003e\u003ca href=\"/our-people/dana-maor\"\u003eDana Maor\u003c/a\u003e\u003c/strong\u003e is a McKinsey senior partner based in Tel Aviv; \u003cstrong\u003eGurneet Singh Dandona\u003c/strong\u003e is an associate partner and a senior expert based in New York; and \u003cstrong\u003eRoland Huyghues-Despointes\u003c/strong\u003e is a consultant based in Paris.\u003c/p\u003e"},"authors":{"targetItems":[{"template":{"id":"3FBABDB63A094F68B1F8E1BBE1BA124E","name":"Author"},"id":"6FA54ADE5D084D4B84C4DF56F435EE33","name":"Eric Hazan","authorTitle":{"value":"Eric Hazan"},"description":{"value":""},"thumbnailImage":{"alt":"","src":null},"profile":{"targetItems":[]}},{"template":{"id":"3FBABDB63A094F68B1F8E1BBE1BA124E","name":"Author"},"id":"D26DABBDC878438F97C7F6F6585FE342","name":"Anu Madgavkar","authorTitle":{"value":"Anu Madgavkar"},"description":{"value":""},"thumbnailImage":{"alt":"","src":null},"profile":{"targetItems":[{"standardImage":{"src":"/~/media/mckinsey/our people/anu madgavkar/anu-madgavkar_profile_1536x1152 august 2017.jpg","alt":"Anu Madgavkar"},"emailLinks":{"value":"Anu_Madgavkar@mckinsey.com"},"linkedInUrl":{"value":"https://www.linkedin.com/pub/anu-madgavkar/14/ba6/7b3"},"description":{"value":"Leads global research focused on sustainable and inclusive growth; labor markets, human capital, and the future of work; technology’s economic impact; digital and financial inclusion; and gender economics"},"locations":{"targetItems":[{"name":"New Jersey","displayName":"New Jersey"}]},"firmTitle":{"value":"McKinsey Global Institute Partner"},"thumbnailImage":{"alt":"Anu Madgavkar","src":"/~/media/mckinsey/our people/anu madgavkar/anu-madgavkar_headshot_988x741 august 2017.jpg"},"url":{"path":"/our-people/anu-madgavkar"}}]}},{"template":{"id":"3FBABDB63A094F68B1F8E1BBE1BA124E","name":"Author"},"id":"36DD0837215D49E78AB6162F78A61DC7","name":"Michael Chui","authorTitle":{"value":"Michael Chui"},"description":{"value":""},"thumbnailImage":{"alt":"","src":null},"profile":{"targetItems":[{"standardImage":{"src":"/~/media/mckinsey/our people/michael chui/michael chui_00168-1_fc-mask_profile_1536x1152.png","alt":""},"emailLinks":{"value":"Michael_Chui@mckinsey.com"},"linkedInUrl":{"value":"https://www.linkedin.com/in/chuimichael"},"description":{"value":"Leads research on the impact of artificial intelligence, information technologies and innovation on business, the economy, and society"},"locations":{"targetItems":[{"name":"Bay Area","displayName":"Bay Area"}]},"firmTitle":{"value":"Senior Fellow"},"thumbnailImage":{"alt":"","src":"/~/media/mckinsey/our people/michael chui/michael chui_00168-1_fc-mask_headshot_988x741.png"},"url":{"path":"/our-people/michael-chui"}}]}},{"template":{"id":"3FBABDB63A094F68B1F8E1BBE1BA124E","name":"Author"},"id":"993A770440604B3CB8DB8929391C3CDD","name":"Sven Smit","authorTitle":{"value":"Sven Smit"},"description":{"value":""},"thumbnailImage":{"alt":"","src":null},"profile":{"targetItems":[{"standardImage":{"src":"/~/media/mckinsey/our people/sven smit/v2/sven-smit_profile_1536x1152.jpg","alt":"Sven Smit"},"emailLinks":{"value":"Sven_Smit@mckinsey.com"},"linkedInUrl":{"value":"https://nl.linkedin.com/in/sven-smit-52ab0675"},"description":{"value":"Leads research on economic and business trends and works with companies to develop business strategies and transformations"},"locations":{"targetItems":[{"name":"Amsterdam","displayName":"Amsterdam"}]},"firmTitle":{"value":"Senior Partner, Chair of Insights and Ecosystems, and Chair of McKinsey Global Institute"},"thumbnailImage":{"alt":"Sven Smit","src":"/~/media/mckinsey/our people/sven smit/v2/sven-smit_headshot_988x741.jpg"},"url":{"path":"/our-people/sven-smit"}}]}},{"template":{"id":"3FBABDB63A094F68B1F8E1BBE1BA124E","name":"Author"},"id":"49390C2F1DC94A3AB8E891F847650A91","name":"Dana Maor","authorTitle":{"value":"Dana Maor"},"description":{"value":"Coheads the People \u0026 Organizational Performance Practice globally and leads it across Europe. 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